Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases.

The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway (BRCA2, ATM and CHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes (HOXB13, CHEK2, BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7, SPDL1, AR, TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.

A deep catalogue of protein-coding variation in 983,578 individuals.

Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.

Protein-truncating variants in BSN are associated with severe adult-onset obesity, type 2 diabetes and fatty liver disease.

Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity.

Genotyping, sequencing and analysis of 140,000 adults from Mexico City.

The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.

Inferring causal genes at type 2 diabetes GWAS loci through chromosome interactions in islet cells.

Background: Resolving causal genes for type 2 diabetes at loci implicated by genome-wide association studies (GWAS) requires integrating functional genomic data from relevant cell types. Chromatin features in endocrine cells of the pancreatic islet are particularly informative and recent studies leveraging chromosome conformation capture (3C) with Hi-C based methods have elucidated regulatory mechanisms in human islets. However, these genome-wide approaches are less sensitive and afford lower resolution than methods that target specific loci. Methods: To gauge the extent to which targeted 3C further resolves chromatin-mediated regulatory mechanisms at GWAS loci, we generated interaction profiles at 23 loci using next-generation (NG) capture-C in a human beta cell model (EndoC-ßH1) and contrasted these maps with Hi-C maps in EndoC-ßH1 cells and human islets and a promoter capture Hi-C map in human islets. Results: We found improvements in assay sensitivity of up to 33-fold and resolved ~3.6X more chromatin interactions. At a subset of 18 loci with 25 co-localised GWAS and eQTL signals, NG Capture-C interactions implicated effector transcripts at five additional genetic signals relative to promoter capture Hi-C through physical contact with gene promoters. Conclusions: High resolution chromatin interaction profiles at selectively targeted loci can complement genome- and promoter-wide maps.

Baseline serum HBV RNA is associated with the risk of hepatitis flare after stopping nucleoside analog therapy in HBeAg-negative participants.

BACKGROUND AND AIMS: HBV RNA in peripheral blood reflects HBV cccDNA transcriptional activity and may predict clinical outcomes. The prospective Melbourne HBV-STOP trial studied nucleot(s)ide analog discontinuation in HBeAg-negative non-cirrhotic participants with long-term virological suppression. Ninety-six weeks after stopping treatment, the proportion of participants with virological relapse (HBV DNA > 2000 IU/mL), biochemical relapse (ALT > 2 × ULN and HBV DNA > 2000 IU/mL), or hepatitis flare (ALT > 5 × ULN and HBV DNA > 2000 IU/mL) was 89%, 58%, and 38%, respectively. We evaluated the ability of serum HBV RNA levels to predict these outcomes. APPROACH RESULTS: HBV RNA levels were measured using the Roche cobas 6800/8800 HBV RNA Investigational Assay. Sixty-five participants had baseline and longitudinal off-treatment specimens available for RNA testing. HBV RNA was detectable at baseline in 25% of participants and was associated with a higher risk of biochemical relapse (81% vs. 51%, p value 0.04) and hepatitis flare (63% vs. 31%, p value 0.04). Participants who had undetectable serum HBV RNA as well as HBsAg ≤ 100 IU/mL at baseline were less likely to experience virological relapse (4 of 9, 44%) than participants with detectable HBV RNA and HBsAg level > 100 IU/mL (15/15, 100%; p value 0.0009). Off-treatment levels of HBV RNA were correlated with HBV DNA and were associated with the risk of hepatitis flare. CONCLUSIONS: Serum HBV RNA may be a useful biomarker for guiding clinical decision-making before stopping nucleot(s)ide analog therapy. Baseline HBV RNA and HBsAg levels are associated with the risk of clinical relapse, hepatitis flare, and disease remission off-treatment.

Rare coding variants in CHRNB2 reduce the likelihood of smoking.

Human genetic studies of smoking behavior have been thus far largely limited to common variants. Studying rare coding variants has the potential to identify drug targets. We performed an exome-wide association study of smoking phenotypes in up to 749,459 individuals and discovered a protective association in CHRNB2, encoding the ß2 subunit of the α4ß2 nicotine acetylcholine receptor. Rare predicted loss-of-function and likely deleterious missense variants in CHRNB2 in aggregate were associated with a 35% decreased odds for smoking heavily (odds ratio (OR) = 0.65, confidence interval (CI) = 0.56-0.76, P = 1.9 × 10-8). An independent common variant association in the protective direction ( rs2072659 ; OR = 0.96; CI = 0.94-0.98; P = 5.3 × 10-6) was also evident, suggesting an allelic series. Our findings in humans align with decades-old experimental observations in mice that ß2 loss abolishes nicotine-mediated neuronal responses and attenuates nicotine self-administration. Our genetic discovery will inspire future drug designs targeting CHRNB2 in the brain for the treatment of nicotine addiction.

A deep catalog of protein-coding variation in 985,830 individuals.

Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.

Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression.

AIMS/HYPOTHESIS: Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. METHODS: A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-ßH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles. RESULTS: CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-ßH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-ßH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function. CONCLUSIONS/INTERPRETATION: Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.

Human genetics uncovers MAP3K15 as an obesity-independent therapeutic target for diabetes.

We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes (P = 5.7 × 10-10) and had lower glycosylated hemoglobin (ß = -0.14 SD units, P = 1.1 × 10-24). These associations were independent of body mass index, suggesting protection against insulin resistance even in the setting of obesity. We replicated these findings in 96,811 Admixed Americans in the Mexico City Prospective Study (P < 0.05)Moreover, the protective effect of MAP3K15 variants was stronger in individuals who did not carry the Latino-enriched SLC16A11 risk haplotype (P = 6.0 × 10-4). Separately, we identified a Finnish-enriched MAP3K15 protein-truncating variant associated with decreased odds of both type 1 and type 2 diabetes (P < 0.05) in FinnGen. No adverse phenotypes were associated with protein-truncating MAP3K15 variants in the UKB, supporting this gene as a therapeutic target for diabetes.

Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes.

Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10-09), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin ßE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.

Abdominal and gluteo-femoral markers of adiposity and risk of vascular-metabolic mortality in a prospective study of 150 000 Mexican adults.

AIMS: Results of previous studies of abdominal adiposity and risk of vascular-metabolic mortality in Hispanic populations have been conflicting. We report results from a large prospective study of Mexican adults with high levels of abdominal adiposity. METHODS AND RESULTS: A total of 159 755 adults aged ≥35 years from Mexico City were enrolled in a prospective study and followed for 16 years. Cox regression, adjusted for confounders, yielded mortality rate ratios (RRs) associated with three markers of abdominal adiposity (waist circumference, waist-hip ratio, and waist-height ratio) and one marker of gluteo-femoral adiposity (hip circumference) for cause-specific mortality before age 75 years. To reduce reverse causality, deaths in the first 5 years of follow-up and participants with diabetes or other prior chronic disease were excluded. Among 113 163 participants without prior disease and aged 35-74 years at recruitment, all adiposity markers were positively associated with vascular-metabolic mortality. Comparing the top versus bottom tenth of the sex-specific distributions, the vascular-metabolic mortality RRs at ages 40-74 years were 2.32 [95% confidence interval (CI) 1.84-2.94] for waist circumference, 2.22 (1.71-2.88) for the waist-hip ratio, 2.63 (2.06-3.36) for the waist-height ratio, and 1.58 (1.29-1.93) for hip circumference. The RRs corresponding to each standard deviation (SD) higher usual levels of these adiposity markers were 1.34 (95% CI 1.27-1.41), 1.31 (1.23-1.39), 1.38 (1.31-1.45), and 1.18 (1.13-1.24), respectively. For the markers of abdominal adiposity, the RRs did not change much after further adjustment for other adiposity markers, but for hip circumference the association was reversed; given body mass index and waist circumference, the RR for vascular-metabolic mortality for each one SD higher usual hip circumference was 0.80 (0.75-0.86). CONCLUSIONS: In this study of Mexican adults, abdominal adiposity (and in particular the waist-height ratio) was strongly and positively associated with vascular-metabolic mortality. For a given amount of general and abdominal adiposity, however, higher hip circumference was associated with lower vascular-metabolic mortality.

TIGER: The gene expression regulatory variation landscape of human pancreatic islets.

Genome-wide association studies (GWASs) identified hundreds of signals associated with type 2 diabetes (T2D). To gain insight into their underlying molecular mechanisms, we have created the translational human pancreatic islet genotype tissue-expression resource (TIGER), aggregating >500 human islet genomic datasets from five cohorts in the Horizon 2020 consortium T2DSystems. We impute genotypes using four reference panels and meta-analyze cohorts to improve the coverage of expression quantitative trait loci (eQTL) and develop a method to combine allele-specific expression across samples (cASE). We identify >1 million islet eQTLs, 53 of which colocalize with T2D signals. Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identify eight cASE colocalizations, among which we found a T2D-associated SLC30A8 variant. We make all data available through the TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translates into therapeutic insight and precision medicine for T2D.

Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity.

Large-scale human exome sequencing can identify rare protein-coding variants with a large impact on complex traits such as body adiposity. We sequenced the exomes of 645,626 individuals from the United Kingdom, the United States, and Mexico and estimated associations of rare coding variants with body mass index (BMI). We identified 16 genes with an exome-wide significant association with BMI, including those encoding five brain-expressed G protein-coupled receptors (CALCR, MC4R, GIPR, GPR151, and GPR75). Protein-truncating variants in GPR75 were observed in ~4/10,000 sequenced individuals and were associated with 1.8 kilograms per square meter lower BMI and 54% lower odds of obesity in the heterozygous state. Knock out of Gpr75 in mice resulted in resistance to weight gain and improved glycemic control in a high-fat diet model. Inhibition of GPR75 may provide a therapeutic strategy for obesity.

Association of Kidney Function With NMR-Quantified Lipids, Lipoproteins, and Metabolic Measures in Mexican Adults.

CONTEXT: Chronic kidney disease (CKD) and diabetes are associated with dyslipidemia, metabolic abnormalities, and atherosclerotic risk. Nuclear magnetic resonance (NMR) spectroscopy provides much more detail on lipoproteins than traditional assays. METHODS: In about 38 000 participants from the Mexico City Prospective Study, aged 35 to 84 years and not using lipid-lowering medication, NMR spectroscopy quantified plasma concentrations of lipoprotein particles, their lipidic compositions, and other metabolic measures. Linear regression related low estimated glomerular filtration rate (eGFR; <60 mL/min/1.73 m2) to each NMR measure after adjustment for confounders and for multiplicity. Analyses were done separately for those with and without diabetes. RESULTS: Among the 38 081 participants (mean age 52 years, 64% women), low eGFR was present for 4.8% (306/6403) of those with diabetes and 1.2% (365/31 678) of those without diabetes. Among both those with and without diabetes, low eGFR was significantly associated with higher levels of 58 NMR measures, including apolipoprotein B (Apo-B), the particle numbers of most Apo-B containing lipoproteins, the cholesterol and triglycerides carried in these lipoproteins, several fatty acids, total cholines and phosphatidylcholine, citrate, glutamine, phenylalanine, ß-OH-butyrate, and the inflammatory measure glycoprotein-A, and significantly lower levels of 13 NMR measures, including medium and small high-density lipoprotein particle measures, very low-density lipoprotein particle size, the ratio of saturated:total fatty acids, valine, tyrosine, and aceto-acetate. CONCLUSIONS: In this Mexican population with high levels of adiposity and diabetes, low kidney function was associated with widespread alterations in lipidic and metabolic profiles, both in those with and without diabetes. These alterations may help explain the higher atherosclerotic risk experienced by people with CKD.

Low-intensity daily smoking and cause-specific mortality in Mexico: prospective study of 150 000 adults.

BACKGROUND: Research is needed to determine the relevance of low-intensity daily smoking to mortality in countries such as Mexico, where such smoking habits are common. METHODS: Prospective study of 159 755 Mexican adults recruited from 1998-2004 and followed for cause-specific mortality to 1 January 2018. Participants were categorized according to baseline self-reported smoking status. Confounder-adjusted mortality rate ratios (RRs) at ages 35-89 were estimated using Cox regression, after excluding those with previous chronic disease (to avoid reverse causality). RESULTS: Among 42 416 men and 86 735 women aged 35-89 and without previous disease, 18 985 men (45%) and 18 072 women (21%) reported current smoking and 8866 men (21%) and 53 912 women (62%) reported never smoking. Smoking less than daily was common: 33% of male current smokers and 39% of female current smokers. During follow-up, the all-cause mortality RRs associated with the baseline smoking categories of <10 cigarettes per day (average during follow-up 4 per day) or ≥10 cigarettes per day (average during follow-up 10 per day), compared with never smoking, were 1.17 (95% confidence interval 1.10-1.25) and 1.54 (1.42-1.67), respectively. RRs were similar irrespective of age or sex. The diseases most strongly associated with daily smoking were respiratory cancers, chronic obstructive pulmonary disease and gastrointestinal and vascular diseases. Ex-daily smokers had substantially lower mortality rates than those who were current daily smokers at recruitment. CONCLUSIONS: In this Mexican population, low-intensity daily smoking was associated with increased mortality. Of those smoking 10 cigarettes per day on average, about one-third were killed by their habit. Quitting substantially reduced these risks.

A Multi-omic Integrative Scheme Characterizes Tissues of Action at Loci Associated with Type 2 Diabetes.

Resolving the molecular processes that mediate genetic risk remains a challenge because most disease-associated variants are non-coding and functional characterization of these signals requires knowledge of the specific tissues and cell-types in which they operate. To address this challenge, we developed a framework for integrating tissue-specific gene expression and epigenomic maps to obtain "tissue-of-action" (TOA) scores for each association signal by systematically partitioning posterior probabilities from Bayesian fine-mapping. We applied this scheme to credible set variants for 380 association signals from a recent GWAS meta-analysis of type 2 diabetes (T2D) in Europeans. The resulting tissue profiles underscored a predominant role for pancreatic islets and, to a lesser extent, adipose and liver, particularly among signals with greater fine-mapping resolution. We incorporated resulting TOA scores into a rule-based classifier and validated the tissue assignments through comparison with data from cis-eQTL enrichment, functional fine-mapping, RNA co-expression, and patterns of physiological association. In addition to implicating signals with a single TOA, we found evidence for signals with shared effects in multiple tissues as well as distinct tissue profiles between independent signals within heterogeneous loci. Lastly, we demonstrated that TOA scores can be directly coupled with eQTL colocalization to further resolve effector transcripts at T2D signals. This framework guides mechanistic inference by directing functional validation studies to the most relevant tissues and can gain power as fine-mapping resolution and cell-specific annotations become richer. This method is generalizable to all complex traits with relevant annotation data and is made available as an R package.

Ex Vivo Murine Skin Model for B. burgdorferi Biofilm.

Borrelia burgdorferi, the causative agent of Lyme disease, has been recently shown to form biofilm structures in vitro and in vivo. Biofilms are tightly clustered microbes characterized as resistant aggregations that allow bacteria to withstand harsh environmental conditions, including the administration of antibiotics. Novel antibiotic combinations have recently been identified for B. burgdorferi in vitro, however, due to prohibiting costs, those agents have not been tested in an environment that can mimic the host tissue. Therefore, researchers cannot evaluate their true effectiveness against B. burgdorferi, especially its biofilm form. A skin ex vivo model system could be ideal for these types of experiments due to its cost effectiveness, reproducibility, and ability to investigate host-microbial interactions. Therefore, the main goal of this study was the establishment of a novel ex vivo murine skin biopsy model for B. burgdorferi biofilm research. Murine skin biopsies were inoculated with B. burgdorferi at various concentrations and cultured in different culture media. Two weeks post-infection, murine skin biopsies were analyzed utilizing immunohistochemical (IHC), reverse transcription PCR (RT-PCR), and various microscopy methods to determine B. burgdorferi presence and forms adopted as well as whether it remained live in the skin tissue explants. Our results showed that murine skin biopsies inoculated with 1 × 107 cells of B. burgdorferi and cultured in BSK-H + 6% rabbit serum media for two weeks yielded not just significant amounts of live B. burgdorferi spirochetes but biofilm forms as well. IHC combined with confocal and atomic force microscopy techniques identified specific biofilm markers and spatial distribution of B. burgdorferi aggregates in the infected skin tissues, confirming that they are indeed biofilms. In the future, this ex vivo skin model can be used to study development and antibiotic susceptibility of B. burgdorferi biofilms in efforts to treat Lyme disease effectively.

Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals.

Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.